AMOS TAKING YOUR RESEARCH TO THE NEXT LEVEL Mara Timofe Research Intern.
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Transcript of AMOS TAKING YOUR RESEARCH TO THE NEXT LEVEL Mara Timofe Research Intern.
SEM – what & why?
SEM = Structural Equation Modeling
a statistical technique for testing and estimating causal relations using a combination of statistical data and qualitative causal assumptions.
Using SEM, you can quickly create models to test hypotheses and confirm relationships among observed and latent variables – moving beyond regression to gain additional insight.
What is the aim of AMOS?
Build structural equation models
(SEM) with more accuracy than
standard multivariate statistics models
using intuitive drag-and-drop
functionality.
What are the advantages of using it?
Quickly build
graphical models
using IBM SPSS Amos’ simple drag-
and-drop drawing
tools
Its approach to multivariate
analysis encompass
es and extends standard methods
builds models that
more realistically
reflect complex
relationships
Its rich, visual
framework lets you to
easily compare,
confirm and refine
models
Medical and healthcare research Confirm which of three variables –
confidence, savings, or research – best predicts a doctor’s support for prescribing generic drugs
Social sciences Study how socioeconomic status,
organizational membership, and other determinants influence differences in voting behavior and political engagement
Educational research Evaluate training program outcomes to
determine impact on classroom effectiveness
Market research Model how customer behavior impacts new
product sales or analyze customer satisfaction and brand loyalty
Business planning Create econometric and financial models
and analyze factors affecting workplace job attainment
Program evaluation Evaluate program outcomes or behavioral
models using SEM to replace traditional stepwise regression
How does it work?
1. Select a data fileInput data from a variety of file formats (IBM® SPSS® Statistics, Micosoft® Excel, text files, or many others). Select grouping variables and group values. IBM SPSS Amos also accepts data in a matrix format if you’ve computed a correlation or covariance matrix
2. Specify your modelUse drag-and-drop drawing tools to quickly specify your path
diagram model. Click on objects in the path diagram to edit values, such as variable names and parameter values. Or simply drag variable names from the variable list to the object in the path diagram to specify variables in your model.
3. Select analysis propertiesSelect the analysis
properties you wish to examine, such as standardized estimates of parameters or squared multiple correlations. Constrain parameters for more precise models by directly specifying path coefficients.
4. View outputBM SPSS Amos
output provides standardized or un-standardized estimates of covariances and regression weights as well as a variety of model fit measures. Hotlinks in the help system link to explanations of the analysis in plain English.